One potential advantage of using Electronic Health Records (EHRs) and other Health Information Technology (HIT) in clinical settings is the ability to quickly process large volumes of data from diverse sources and identify potential problems. Many HIT systems include, for example, Clinical Order Entry (COE) subsystems, which allow a clinician to order tests or medications for a patient. Those HIT systems may also include Clinical Conflict Check (CCC) subsystems, which acquire relevant data from within the HIT system and alert the clinician to inconsistencies or potential problems. For example, CCCs may alert clinicians to duplicate orders, potential undesirable drug interactions, incongruent data entry (e.g., observations related to the tonsils in a patient who has had a tonsillectomy) and other facially problematic data or order entries. CCCs may also alert clinicians to items of information like known patient allergies or risk factors that may influence the course of a patient encounter or a treatment plan.
The alerts are meant to improve healthcare efficiency and patient outcomes. Identifying duplicate orders, for example, could avoid the expense and delay associated with repeating a recently completed medical test, or avoid an accidental drug overdose. As another example, identifying possible undesirable drug interactions may prevent adverse events, particularly when a patient is taking many medications, or is taking medications prescribed by two or more clinicians. Unfortunately, empirical data suggests that such alerts are often ignored. In some systems, over 95% of medical order alerts are overridden or ignored. While this suggests that a small percentage of medical order alerts are valid and acted upon to prevent potential problems, the proportion of alerts that are acted upon suggests that conventional alerts are often not useful.
There remains a need for a clinical HIT system that provides meaningful, actionable alerts.